Knowledge Graphs (KGs) have become a popular format of data representation, mainly due to their flexible data model which renders them particularly suited to those tasks where data coming from multiple, possibly heterogeneous, sources has to be integrated in order to be fully exploited. KGs have received both the attention of academia, through foundational efforts stemming from scientific literature such as Knowledge Representation, Machine Learning, or Databases, and the enterprise world. Enterprise applications, in particular, exploit tools implementing recommendations from the Semantic Web community (such as RDF or OWL), and proprietary formats based on property graphs. The general data model of KGs allows for representing both extensional knowledge, the data itself, and intensional information made available by domain ontologies. Hence, KGs provide a way to enrich data coming from legacy sources with semantic information coming from the application domain. This empowers users with automated inference, enriches interpretability of data, and overall facilitates access and integration.

The aim of the present Research Topic is to provide a dedicated venue for authors working in the context of semantic technologies for KGs where the focus is both on data and ontologies. Currently, many venues are very focused on the former (e.g., the whole Database community), or the latter (e.g., the Knowledge Representation or Semantic Web communities). However, initiatives focusing on leveraging semantic technologies for data management necessitate an integrated perspective that merges data with semantics. This also calls for bespoke techniques that seamlessly combine the two. In parallel, we plan to propose a workshop centered on the themes of this Research Topic, aspiring to create a community that excels in both data management and semantic technologies.

This Research Topic welcomes submissions of papers relevant to the application of Semantic Technologies for data management, including research on foundational aspects as well as in-use solutions.

Topics of interest include, but are not limited to:

- Knowledge Graphs (KGs)
- Virtual Knowledge Graphs (VKGs)/Ontology-Based Data Access (OBDA)
- Ontology-Mediated Query Answering (OMQA)
- (V)KG Refinement
- (V)KGs Construction, Enrichment, Integration
- (V)KGs Integration
- Management and exploitation of provenance in (V)KGs
- Ontologies, metadata vocabularies, and standardization
- Semantic technologies applied to data infrastructures and FAIR data management
- Effective Query Rewriting and Optimization
- Performance and Security in (V)KGs
- Mappings and Ontology Bootstrapping
- Mappings Design, Management, and Specification
- Management of the evolution and preservation of (V)KGs
- Semantic Technologies for Data-centric AI

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Frontiers in Computer Science

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